Principles and Techniques for the Professional Data Analyst
By Dean Abbott
Final Release Date: March 2014
Learn the art and science of predictive analytics — techniques that get results
Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling. Hands-on examples and case studies are included.
The ability to successfully apply predictive analytics enables businesses to effectively interpret big data; essential for competition today
This guide teaches not only the principles of predictive analytics, but also how to apply them to achieve real, pragmatic solutions
Explains methods, principles, and techniques for conducting predictive analytics projects from start to finish
Illustrates each technique with hands-on examples and includes as series of in-depth case studies that apply predictive analytics to common business scenarios
A companion website provides all the data sets used to generate the examples as well as a free trial version of software
Applied Predictive Analytics arms data and business analysts and business managers with the tools they need to interpret and capitalize on big data.
Comments about oreilly Applied Predictive Analytics:
This book is written by one of the leading experts in applied predictive analytics, and it shows on every page.
The examples are very hands-on, yet tool-agnostic, the guidance is concise and just deep enough to be useful (look elsewhere for greater detail), and the comparisons with related fields like statistics, data mining and BI are one of a kind.
I would have ticked "easy to understand" very happily as well, but this book does require some degree of specialist expertise to be used to its full advantage. Then again, there's no other book I'd rather recommend to a technically and/or quantitatively inclined audience.
All in all, someone had to write this book, and I'm very happy Dean took on the task.
Bottom Line Yes, I would recommend this to a friend